MCP server · source category: Data Science Tools
mrnh/rigor
Classical hypothesis testing, effect sizes, power and sample-size analysis and multiple-comparisons correction, returned a…
Classical hypothesis testing, effect sizes, power and sample-size analysis and multiple-comparisons correction, returned as cited, assumption-checked answers.
Record
- Type
- MCP server
- Category
- AI & Machine Learning
- Authentication
- No authentication
- Pricing
- Free
- Documentation
- https://github.com/mrnh/rigor
- Repository
- https://github.com/mrnh/rigor
Fields are reproduced from the source registry as-is. “Unknown” means the source did not describe the field — it is not an inference. See the methodology for how records are collected and normalised.
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